Image or waveform analysis method, system and non-transitory computer-readable storage medium

Abstract

A method of interpreting images and/or waveforms determines differences between populations, input sources and/or test subjects. The method includes operations. The operations include receiving a first set of data from at least one of the input sources; encoding the first received data into a first lower dimensional representation; receiving a second set of data from the at least one of the input sources or from a second input source; encoding the second received data into a second lower dimensional representation; comparing the first low dimensional representation with the second low dimensional representation to generate a reconstruction; decoding the representation to reconstruct the data into a format similar to that of the received data; and transmitting a signal corresponding to the decoded representation. Related devices, apparatuses, systems, techniques, articles and non-transitory computer-readable storage medium are also described.

What is claimed is: 
     
         1 . A method of interpreting images and/or waveforms to determine differences between populations, input sources and/or test subjects, wherein a device is provided, the device having at least one processor and a memory storing at least one program for execution by the at least one processor, the at least one program including instructions, which, when executed by the at least one processor cause the at least one processor to perform operations comprising:
 receiving a first set of data from at least one of the input sources;   encoding the first received data into a first lower dimensional representation;   receiving a second set of data from the at least one of the input sources or from a second input source;   encoding the second received data into a second lower dimensional representation;   comparing the first low dimensional representation with the second low dimensional representation to generate a reconstruction;   decoding the representation to reconstruct the data into a format similar to that of the received data; and   transmitting a signal corresponding to the decoded representation.   
     
     
         2 . The method of  claim 1 , wherein the first set of data and/or the second set of data comprises one or more of an electronic health record (EHR), an electrocardiogram (ECG), a speech waveform, a spectrogram, and an electroencephalogram (EEG). 
     
     
         3 . The method of  claim 2 , wherein the first set of data and/or the second set of data comprises the ECG, and wherein heart beats and fiducial markers are identified in the decoded representation. 
     
     
         4 . The method of  claim 2 , wherein the first set of data and/or the second set of data comprises the ECG, and wherein an arrhythmia is identified from the decoded representation. 
     
     
         5 . The method of  claim 2 , wherein the first set of data and/or the second set of data comprises the speech waveform, and wherein differences relative to a standard pronunciation are identified in the decoded representation. 
     
     
         6 . The method of  claim 2 , wherein the first set of data and/or the second set of data comprises the speech waveform, and wherein at least one anatomical structure is associated with at least one segment of the decoded representation. 
     
     
         7 . The method of  claim 2 , wherein the first set of data and/or the second set of data comprises the EEG, and wherein at least one pathology is associated with one or more segments of the decoded representation. 
     
     
         8 . The method of  claim 1 , wherein the first lower dimensional representation and/or the second lower dimensional representation is encoded with one or more of a perturbation, a compactless loss, and a cross-entropy for classification. 
     
     
         9 . The method of  claim 1 , wherein the reconstruction is generated with generative adversarial reconstruction (GAN). 
     
     
         10 . The method of  claim 1 , wherein the signal is analyzed to highlight the differences between the populations, the input sources or the test subjects. 
     
     
         11 . The method of  claim 1 , wherein the signal is analyzed with a decision exploration (DE) model to generate a decision. 
     
     
         12 . The method of  claim 11 , wherein the decision includes one or more of an admission decision, a readmission decision, a risk of mortality, and a diagnosis code. 
     
     
         13 . The method of  claim 12 , wherein the diagnosis code comprises an International Classification of Diseases (ICD) code. 
     
     
         14 . The method of  claim 1 , wherein the representation is a blobby representation, and the decoded representation is a decoded blobby representation. 
     
     
         15 . A system for interpreting images and/or waveforms to determine differences between populations, input sources and/or test subjects, the system comprising:
 a device having at least one processor and a memory storing at least one program for execution by the at least one processor, the at least one program including instructions, when, executed by the at least one processor cause the at least one processor to perform operations comprising:   receiving a first set of data from at least one of the input sources;   encoding the first received data into a first lower dimensional representation;   receiving a second set of data from the at least one of the input sources or from a second input source;   encoding the second received data into a second lower dimensional representation;   comparing the first low dimensional representation with the second low dimensional representation to generate a reconstruction;   decoding the representation to reconstruct the data into a format similar to that of the received data; and   transmitting a signal corresponding to the decoded representation.   
     
     
         16 . The system of  claim 15 , wherein the first set of data and/or the second set of data comprises one or more of an electronic health record (EHR), an electrocardiogram (ECG), a speech waveform, a spectrogram, and an electroencephalogram (EEG). 
     
     
         17 . The system of  claim 16 , wherein the first set of data and/or the second set of data comprises the ECG, and wherein heart beats and fiducial markers are identified in the decoded representation. 
     
     
         18 . The system of  claim 16 , wherein the first set of data and/or the second set of data comprises the ECG, and wherein an arrhythmia is identified from the decoded representation. 
     
     
         19 . The system of  claim 16 , wherein the first set of data and/or the second set of data comprises the speech waveform, and wherein differences relative to a standard pronunciation are identified in the decoded representation. 
     
     
         20 . The system of  claim 16 , wherein the first set of data and/or the second set of data comprises the speech waveform, and wherein at least one anatomical structure is associated with at least one segment of the decoded representation. 
     
     
         21 . The system of  claim 16 , wherein the first set of data and/or the second set of data comprises the EEG, and wherein at least one pathology is associated with one or more segments of the decoded representation. 
     
     
         22 . The system of  claim 15 , wherein the first lower dimensional representation and/or the second lower dimensional representation is encoded with one or more of a perturbation, a compactless loss, and a cross-entropy for classification. 
     
     
         23 . The system of  claim 15 , wherein the reconstruction is generated with generative adversarial reconstruction (GAN). 
     
     
         24 . The system of  claim 15 , wherein the signal is analyzed to highlight the differences between the populations, the input sources or the test subjects. 
     
     
         25 . The system of  claim 15 , wherein the signal is analyzed with a decision exploration (DE) model to generate a decision. 
     
     
         26 . The system of  claim 25 , wherein the decision includes one or more of an admission decision, a readmission decision, a risk of mortality, and a diagnosis code. 
     
     
         27 . The system of  claim 26 , wherein the diagnosis code comprises an International Classification of Diseases (ICD) code. 
     
     
         28 . The system of  claim 15 , wherein the representation is a blobby representation, and the decoded representation is a decoded blobby representation. 
     
     
         29 . A non-transitory computer-readable storage medium storing at least one program for interpreting images and/or waveforms to determine differences between populations, input sources and/or test subjects, the at least one program for execution by at least one processor and a memory storing the at least one program, the at least one program including instructions, when, executed by the at least one processor cause the at least one processor to perform operations comprising:
 receiving a first set of data from at least one of the input sources;   encoding the first received data into a first lower dimensional representation;   receiving a second set of data from the at least one of the input sources or from a second input source;   encoding the second received data into a second lower dimensional representation;   comparing the first low dimensional representation with the second low dimensional representation to generate a reconstruction;   decoding the representation to reconstruct the data into a format similar to that of the received data; and   transmitting a signal corresponding to the decoded representation.   
     
     
         30 . The non-transitory computer-readable storage medium of  claim 29 , wherein the first set of data and/or the second set of data comprises one or more of an electronic health record (EHR), an electrocardiogram (ECG), a speech waveform, a spectrogram, and an electroencephalogram (EEG). 
     
     
         31 . The non-transitory computer-readable storage medium of  claim 30 , wherein the first set of data and/or the second set of data comprises the ECG, and wherein heart beats and fiducial markers are identified in the decoded representation. 
     
     
         32 . The non-transitory computer-readable storage medium of  claim 30 , wherein the first set of data and/or the second set of data comprises the ECG, and wherein an arrhythmia is identified from the decoded representation. 
     
     
         33 . The non-transitory computer-readable storage medium of  claim 30 , wherein the first set of data and/or the second set of data comprises the speech waveform, and wherein differences relative to a standard pronunciation are identified in the decoded representation. 
     
     
         34 . The non-transitory computer-readable storage medium of  claim 30 , wherein the first set of data and/or the second set of data comprises the speech waveform, and wherein at least one anatomical structure is associated with at least one segment of the decoded representation. 
     
     
         35 . The non-transitory computer-readable storage medium of  claim 30 , wherein the first set of data and/or the second set of data comprises the EEG, and wherein at least one pathology is associated with one or more segments of the decoded representation. 
     
     
         36 . The non-transitory computer-readable storage medium of  claim 29 , wherein the first lower dimensional representation and/or the second lower dimensional representation is encoded with one or more of a perturbation, a compactless loss, and a cross-entropy for classification. 
     
     
         37 . The non-transitory computer-readable storage medium of  claim 29 , wherein the reconstruction is generated with generative adversarial reconstruction (GAN). 
     
     
         38 . The non-transitory computer-readable storage medium of  claim 29 , wherein the signal is analyzed to highlight the differences between the populations, the input sources or the test subjects. 
     
     
         39 . The non-transitory computer-readable storage medium of  claim 29 , wherein the signal is analyzed with a decision exploration (DE) model to generate a decision. 
     
     
         40 . The non-transitory computer-readable storage medium of  claim 39 , wherein the decision includes one or more of an admission decision, a readmission decision, a risk of mortality, and a diagnosis code. 
     
     
         41 . The non-transitory computer-readable storage medium of  claim 40 , wherein the diagnosis code comprises an International Classification of Diseases (ICD) code. 
     
     
         42 . The non-transitory computer-readable storage medium of  claim 29 , wherein the representation is a blobby representation, and the decoded representation is a decoded blobby representation.